{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# statsmodels Principal Component Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Key ideas:* Principal component analysis, world bank data, fertility\n",
    "\n",
    "In this notebook, we use principal components analysis (PCA) to analyze the time series of fertility rates in 192 countries, using data obtained from the World Bank.  The main goal is to understand how the trends in fertility over time differ from country to country.  This is a slightly atypical illustration of PCA because the data are time series.  Methods such as functional PCA have been developed for this setting, but since the fertility data are very smooth, there is no real disadvantage to using standard PCA in this case."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import statsmodels.api as sm\n",
    "from statsmodels.multivariate.pca import PCA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The data can be obtained from the [World Bank web site](http://data.worldbank.org/indicator/SP.DYN.TFRT.IN), but here we work with a slightly cleaned-up version of the data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country Name</th>\n",
       "      <th>Country Code</th>\n",
       "      <th>Indicator Name</th>\n",
       "      <th>Indicator Code</th>\n",
       "      <th>1960</th>\n",
       "      <th>1961</th>\n",
       "      <th>1962</th>\n",
       "      <th>1963</th>\n",
       "      <th>1964</th>\n",
       "      <th>1965</th>\n",
       "      <th>...</th>\n",
       "      <th>2004</th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Aruba</td>\n",
       "      <td>ABW</td>\n",
       "      <td>Fertility rate, total (births per woman)</td>\n",
       "      <td>SP.DYN.TFRT.IN</td>\n",
       "      <td>4.820</td>\n",
       "      <td>4.655</td>\n",
       "      <td>4.471</td>\n",
       "      <td>4.271</td>\n",
       "      <td>4.059</td>\n",
       "      <td>3.842</td>\n",
       "      <td>...</td>\n",
       "      <td>1.786</td>\n",
       "      <td>1.769</td>\n",
       "      <td>1.754</td>\n",
       "      <td>1.739</td>\n",
       "      <td>1.726</td>\n",
       "      <td>1.713</td>\n",
       "      <td>1.701</td>\n",
       "      <td>1.690</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Andorra</td>\n",
       "      <td>AND</td>\n",
       "      <td>Fertility rate, total (births per woman)</td>\n",
       "      <td>SP.DYN.TFRT.IN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.240</td>\n",
       "      <td>1.180</td>\n",
       "      <td>1.250</td>\n",
       "      <td>1.190</td>\n",
       "      <td>1.220</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>Fertility rate, total (births per woman)</td>\n",
       "      <td>SP.DYN.TFRT.IN</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>...</td>\n",
       "      <td>7.136</td>\n",
       "      <td>6.930</td>\n",
       "      <td>6.702</td>\n",
       "      <td>6.456</td>\n",
       "      <td>6.196</td>\n",
       "      <td>5.928</td>\n",
       "      <td>5.659</td>\n",
       "      <td>5.395</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Angola</td>\n",
       "      <td>AGO</td>\n",
       "      <td>Fertility rate, total (births per woman)</td>\n",
       "      <td>SP.DYN.TFRT.IN</td>\n",
       "      <td>7.316</td>\n",
       "      <td>7.354</td>\n",
       "      <td>7.385</td>\n",
       "      <td>7.410</td>\n",
       "      <td>7.425</td>\n",
       "      <td>7.430</td>\n",
       "      <td>...</td>\n",
       "      <td>6.704</td>\n",
       "      <td>6.657</td>\n",
       "      <td>6.598</td>\n",
       "      <td>6.523</td>\n",
       "      <td>6.434</td>\n",
       "      <td>6.331</td>\n",
       "      <td>6.218</td>\n",
       "      <td>6.099</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Albania</td>\n",
       "      <td>ALB</td>\n",
       "      <td>Fertility rate, total (births per woman)</td>\n",
       "      <td>SP.DYN.TFRT.IN</td>\n",
       "      <td>6.186</td>\n",
       "      <td>6.076</td>\n",
       "      <td>5.956</td>\n",
       "      <td>5.833</td>\n",
       "      <td>5.711</td>\n",
       "      <td>5.594</td>\n",
       "      <td>...</td>\n",
       "      <td>2.004</td>\n",
       "      <td>1.919</td>\n",
       "      <td>1.849</td>\n",
       "      <td>1.796</td>\n",
       "      <td>1.761</td>\n",
       "      <td>1.744</td>\n",
       "      <td>1.741</td>\n",
       "      <td>1.748</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 58 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Country Name Country Code                            Indicator Name  \\\n",
       "0        Aruba          ABW  Fertility rate, total (births per woman)   \n",
       "1      Andorra          AND  Fertility rate, total (births per woman)   \n",
       "2  Afghanistan          AFG  Fertility rate, total (births per woman)   \n",
       "3       Angola          AGO  Fertility rate, total (births per woman)   \n",
       "4      Albania          ALB  Fertility rate, total (births per woman)   \n",
       "\n",
       "   Indicator Code   1960   1961   1962   1963   1964   1965  ...    2004  \\\n",
       "0  SP.DYN.TFRT.IN  4.820  4.655  4.471  4.271  4.059  3.842  ...   1.786   \n",
       "1  SP.DYN.TFRT.IN    NaN    NaN    NaN    NaN    NaN    NaN  ...     NaN   \n",
       "2  SP.DYN.TFRT.IN  7.671  7.671  7.671  7.671  7.671  7.671  ...   7.136   \n",
       "3  SP.DYN.TFRT.IN  7.316  7.354  7.385  7.410  7.425  7.430  ...   6.704   \n",
       "4  SP.DYN.TFRT.IN  6.186  6.076  5.956  5.833  5.711  5.594  ...   2.004   \n",
       "\n",
       "    2005   2006   2007   2008   2009   2010   2011  2012  2013  \n",
       "0  1.769  1.754  1.739  1.726  1.713  1.701  1.690   NaN   NaN  \n",
       "1    NaN  1.240  1.180  1.250  1.190  1.220    NaN   NaN   NaN  \n",
       "2  6.930  6.702  6.456  6.196  5.928  5.659  5.395   NaN   NaN  \n",
       "3  6.657  6.598  6.523  6.434  6.331  6.218  6.099   NaN   NaN  \n",
       "4  1.919  1.849  1.796  1.761  1.744  1.741  1.748   NaN   NaN  \n",
       "\n",
       "[5 rows x 58 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = sm.datasets.fertility.load_pandas().data\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we construct a DataFrame that contains only the numerical fertility rate data and set the index to the country names.  We also drop all the countries with any missing data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>1960</th>\n",
       "      <th>1961</th>\n",
       "      <th>1962</th>\n",
       "      <th>1963</th>\n",
       "      <th>1964</th>\n",
       "      <th>1965</th>\n",
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       "      <th>1969</th>\n",
       "      <th>...</th>\n",
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       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Aruba</th>\n",
       "      <td>4.820</td>\n",
       "      <td>4.655</td>\n",
       "      <td>4.471</td>\n",
       "      <td>4.271</td>\n",
       "      <td>4.059</td>\n",
       "      <td>3.842</td>\n",
       "      <td>3.625</td>\n",
       "      <td>3.417</td>\n",
       "      <td>3.226</td>\n",
       "      <td>3.054</td>\n",
       "      <td>...</td>\n",
       "      <td>1.825</td>\n",
       "      <td>1.805</td>\n",
       "      <td>1.786</td>\n",
       "      <td>1.769</td>\n",
       "      <td>1.754</td>\n",
       "      <td>1.739</td>\n",
       "      <td>1.726</td>\n",
       "      <td>1.713</td>\n",
       "      <td>1.701</td>\n",
       "      <td>1.690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>7.671</td>\n",
       "      <td>...</td>\n",
       "      <td>7.484</td>\n",
       "      <td>7.321</td>\n",
       "      <td>7.136</td>\n",
       "      <td>6.930</td>\n",
       "      <td>6.702</td>\n",
       "      <td>6.456</td>\n",
       "      <td>6.196</td>\n",
       "      <td>5.928</td>\n",
       "      <td>5.659</td>\n",
       "      <td>5.395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Angola</th>\n",
       "      <td>7.316</td>\n",
       "      <td>7.354</td>\n",
       "      <td>7.385</td>\n",
       "      <td>7.410</td>\n",
       "      <td>7.425</td>\n",
       "      <td>7.430</td>\n",
       "      <td>7.422</td>\n",
       "      <td>7.403</td>\n",
       "      <td>7.375</td>\n",
       "      <td>7.339</td>\n",
       "      <td>...</td>\n",
       "      <td>6.778</td>\n",
       "      <td>6.743</td>\n",
       "      <td>6.704</td>\n",
       "      <td>6.657</td>\n",
       "      <td>6.598</td>\n",
       "      <td>6.523</td>\n",
       "      <td>6.434</td>\n",
       "      <td>6.331</td>\n",
       "      <td>6.218</td>\n",
       "      <td>6.099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albania</th>\n",
       "      <td>6.186</td>\n",
       "      <td>6.076</td>\n",
       "      <td>5.956</td>\n",
       "      <td>5.833</td>\n",
       "      <td>5.711</td>\n",
       "      <td>5.594</td>\n",
       "      <td>5.483</td>\n",
       "      <td>5.376</td>\n",
       "      <td>5.268</td>\n",
       "      <td>5.160</td>\n",
       "      <td>...</td>\n",
       "      <td>2.195</td>\n",
       "      <td>2.097</td>\n",
       "      <td>2.004</td>\n",
       "      <td>1.919</td>\n",
       "      <td>1.849</td>\n",
       "      <td>1.796</td>\n",
       "      <td>1.761</td>\n",
       "      <td>1.744</td>\n",
       "      <td>1.741</td>\n",
       "      <td>1.748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United Arab Emirates</th>\n",
       "      <td>6.928</td>\n",
       "      <td>6.910</td>\n",
       "      <td>6.893</td>\n",
       "      <td>6.877</td>\n",
       "      <td>6.861</td>\n",
       "      <td>6.841</td>\n",
       "      <td>6.816</td>\n",
       "      <td>6.783</td>\n",
       "      <td>6.738</td>\n",
       "      <td>6.679</td>\n",
       "      <td>...</td>\n",
       "      <td>2.428</td>\n",
       "      <td>2.329</td>\n",
       "      <td>2.236</td>\n",
       "      <td>2.149</td>\n",
       "      <td>2.071</td>\n",
       "      <td>2.004</td>\n",
       "      <td>1.948</td>\n",
       "      <td>1.903</td>\n",
       "      <td>1.868</td>\n",
       "      <td>1.841</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 52 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       1960   1961   1962   1963   1964   1965   1966   1967  \\\n",
       "Country Name                                                                   \n",
       "Aruba                 4.820  4.655  4.471  4.271  4.059  3.842  3.625  3.417   \n",
       "Afghanistan           7.671  7.671  7.671  7.671  7.671  7.671  7.671  7.671   \n",
       "Angola                7.316  7.354  7.385  7.410  7.425  7.430  7.422  7.403   \n",
       "Albania               6.186  6.076  5.956  5.833  5.711  5.594  5.483  5.376   \n",
       "United Arab Emirates  6.928  6.910  6.893  6.877  6.861  6.841  6.816  6.783   \n",
       "\n",
       "                       1968   1969  ...     2002   2003   2004   2005   2006  \\\n",
       "Country Name                        ...                                        \n",
       "Aruba                 3.226  3.054  ...    1.825  1.805  1.786  1.769  1.754   \n",
       "Afghanistan           7.671  7.671  ...    7.484  7.321  7.136  6.930  6.702   \n",
       "Angola                7.375  7.339  ...    6.778  6.743  6.704  6.657  6.598   \n",
       "Albania               5.268  5.160  ...    2.195  2.097  2.004  1.919  1.849   \n",
       "United Arab Emirates  6.738  6.679  ...    2.428  2.329  2.236  2.149  2.071   \n",
       "\n",
       "                       2007   2008   2009   2010   2011  \n",
       "Country Name                                             \n",
       "Aruba                 1.739  1.726  1.713  1.701  1.690  \n",
       "Afghanistan           6.456  6.196  5.928  5.659  5.395  \n",
       "Angola                6.523  6.434  6.331  6.218  6.099  \n",
       "Albania               1.796  1.761  1.744  1.741  1.748  \n",
       "United Arab Emirates  2.004  1.948  1.903  1.868  1.841  \n",
       "\n",
       "[5 rows x 52 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "columns = list(map(str, range(1960, 2012)))\n",
    "data.set_index('Country Name', inplace=True)\n",
    "dta = data[columns]\n",
    "dta = dta.dropna()\n",
    "dta.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are two ways to use PCA to analyze a rectangular matrix: we can treat the rows as the \"objects\" and the columns as the \"variables\", or vice-versa.  Here we will treat the fertility measures as \"variables\" used to measure the countries as \"objects\".  Thus the goal will be to reduce the yearly fertility rate values to a small number of fertility rate \"profiles\" or \"basis functions\" that capture most of the variation over time in the different countries."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The mean trend is removed in PCA, but its worthwhile taking a look at it.  It shows that fertility has dropped steadily over the time period covered in this dataset.  Note that the mean is calculated using a country as the unit of analysis, ignoring population size.  This is also true for the PC analysis conducted below.  A more sophisticated analysis might weight the countries, say by population in 1980."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 51)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = dta.mean().plot(grid=False)\n",
    "ax.set_xlabel(\"Year\", size=17)\n",
    "ax.set_ylabel(\"Fertility rate\", size=17);\n",
    "ax.set_xlim(0, 51)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next we perform the PCA:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "pca_model = PCA(dta.T, standardize=False, demean=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Based on the eigenvalues, we see that the first PC dominates, with perhaps a small amount of meaningful variation captured in the second and third PC's."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = pca_model.plot_scree(log_scale=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next we will plot the PC factors.  The dominant factor is monotonically increasing.  Countries with a positive score on the first factor will increase faster (or decrease slower) compared to the mean shown above.  Countries with a negative score on the first factor will decrease faster than the mean.  The second factor is U-shaped with a positive peak at around 1985.  Countries with a large positive score on the second factor will have lower than average fertilities at the beginning and end of the data range, but higher than average fertility in the middle of the range."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 4))\n",
    "lines = ax.plot(pca_model.factors.iloc[:,:3], lw=4, alpha=.6)\n",
    "ax.set_xticklabels(dta.columns.values[::10])\n",
    "ax.set_xlim(0, 51)\n",
    "ax.set_xlabel(\"Year\", size=17)\n",
    "fig.subplots_adjust(.1, .1, .85, .9)\n",
    "legend = fig.legend(lines, ['PC 1', 'PC 2', 'PC 3'], loc='center right')\n",
    "legend.draw_frame(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To better understand what is going on, we will plot the fertility trajectories for sets of countries with similar PC scores.  The following convenience function produces such a plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "idx = pca_model.loadings.iloc[:,0].argsort()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we plot the five countries with the greatest scores on PC 1.  These countries have a higher rate of fertility increase than the global mean (which is decreasing)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def make_plot(labels):\n",
    "    fig, ax = plt.subplots(figsize=(9,5))\n",
    "    ax = dta.loc[labels].T.plot(legend=False, grid=False, ax=ax)\n",
    "    dta.mean().plot(ax=ax, grid=False, label='Mean')\n",
    "    ax.set_xlim(0, 51);\n",
    "    fig.subplots_adjust(.1, .1, .75, .9)\n",
    "    ax.set_xlabel(\"Year\", size=17)\n",
    "    ax.set_ylabel(\"Fertility\", size=17);\n",
    "    legend = ax.legend(*ax.get_legend_handles_labels(), loc='center left', bbox_to_anchor=(1, .5))\n",
    "    legend.draw_frame(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = dta.index[idx[-5:]]\n",
    "make_plot(labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here are the five countries with the greatest scores on factor 2.  These are countries that reached peak fertility around 1980, later than much of the rest of the world, followed by a rapid decrease in fertility."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "idx = pca_model.loadings.iloc[:,1].argsort()\n",
    "make_plot(dta.index[idx[-5:]])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally we have the countries with the most negative scores on PC 2.  These are the countries where the fertility rate declined much faster than the global mean during the 1960's and 1970's, then flattened out."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "make_plot(dta.index[idx[:5]])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also look at a scatterplot of the first two principal component scores.  We see that the variation among countries is fairly continuous, except perhaps that the two countries with highest scores for PC 2 are somewhat separated from the other points.  These countries, Oman and Yemen, are unique in having a sharp spike in fertility around 1980.  No other country has such a spike.  In contrast, the countries with high scores on PC 1 (that have continuously increasing fertility), are part of a continuum of variation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Oman', 'Yemen, Rep.'], dtype=object)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "pca_model.loadings.plot.scatter(x='comp_00',y='comp_01', ax=ax)\n",
    "ax.set_xlabel(\"PC 1\", size=17)\n",
    "ax.set_ylabel(\"PC 2\", size=17)\n",
    "dta.index[pca_model.loadings.iloc[:, 1] > .2].values"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
